Categories: Paid Media

How to Use Google Ads Match Types

Google Ads allows you to specify a match type for each keyword you bid on. Yahoo and Bing do too, though there are some slight variations in how they work.  The three match types in Google are exact, phrase, and broad.  The match type you choose tells the search engine when to match a user’s query to your keyword. Here’s how each match type works:

  • Exact: your ad will be served when and only when a user enters the keyword you purchased. If you want to make a keyword exact match, you put square brackets around it when you enter it.
  • Phrase: your ad will be served when a user enters a phrase that includes the keywords you purchased in the same order. For example, if you bid on “house music”, your ad will match the query “download house music”, but not the query “new orleans music house”. If you want to make a keyword phrase match, you put quotes around it when you enter it.
  • Broad: your ad will be served when a user enters a phrase that includes the keywords you purchased, and not necessarily in the same order. Your ad will also be served when a user enters a phrase that Google deems equivalent to your keywords, such as misspellings, synonyms or pluralizations. For example, if you bid on “denver taxidermy”, your ad will likely match the following queries:
    • “taxidermy denver”
    • “denver taxidermists”
    • “a taxidermist near denver”

    Broad match is the default, so you don’t have to do anything to specify broad match.

Think of match types like funnels. Broad matching is like a big, wide funnel that catches lots of queries. Phrase matching is like a medium-sized funnel that catches more queries than exact, but fewer than broad. Exact matching is like a funnel that doesn’t get any wider at the top, which isn’t much good as a funnel.

Also, while they don’t behave quite like match types, you can add negative keywords to an ad group or campaign. A negative keyword tells Google not to serve an ad when that keyword is present in the query. For example, if you created an ad group with the broad match keyword “denver taxidermy” and the negative keyword “squirrel”, Google would not serve your ad if someone searched for “denver squirrel taxidermy”. If you want to add a negative keyword, you put a minus sign before the keyword with no space, e.g. “-squirrel”.

Here’s a crazy stat: people search 200 million keywords in Google that have never been searched before every single day*. That probably puts the total number of unique queries that have ever been done on Google somewhere in the hundreds of billions. Your goal is to get your ads to show for any of those queries that are relevant to the products or services you sell. The broad match type is the best way to do that, and is what I use most of the time. But broad matching can also result in irrelevant traffic, so it’s a good idea to keep an eye on what keywords are driving visits to your site and add negative keywords where necessary. Most web analytics tools have a report that shows referring keywords, and the Google AdWords Search Query Performance Report shows some of the search phrases that were matched to your ad.

One trick I sometimes do is to add both an exact match version and a broad match version of the same keyword to an ad group. This allows me to see the performance of the exact match version, which is often better than the broad match version. Over time, I will bid up the exact match version if it is getting better results. For more on keyword bidding based on performance, see our article Paid Search Bidding Based on ROI.

It’s also not a good idea to just trust broad matching and not bother creating ads with variations of keywords you know are relevant to your business. Broad matching is a good way to catch keywords you don’t expect, but you should include any you do know about in your campaign. Doing so will help you understand the performance of each variation, and you can achieve higher quality scores by ensuring that text ads and landing pages are well-matched to each keyword.

*This stat is derived from search query data in these two posts: This week in search 1/8/10 and By the Numbers: Twitter vs Facebook vs Google Buzz

Nico Brooks

Nico loves marketing analytics, running, and analytics about running. He's Two Octobers' Head of Analytics, and loves teaching. Learn more about Nico or read more blogs he has written.

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